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Mobile Networks and Applications

, Volume 24, Issue 6, pp 1985–1993 | Cite as

Joint Time and Node Optimization for Cluster-Based Energy-Efficient Cognitive Internet of Things

  • Xin Liu
  • Min JiaEmail author
  • Zhenyu Na
Article
  • 36 Downloads

Abstract

In order to solve the problem of scarce spectrum resources of Internet of things (IoT), cognitive IoT (CIoT) based on cognitive radio (CR) has been put forwarded to improve the spectrum utilization of IoT through using the idle spectrum of primary user (PU). In this paper, a cluster-based energy-efficient CIoT is proposed to improve both spectrum efficiency and energy efficiency of IoT, which can harvest the radio frequency (RF) energy of the PU to supply energy consumption of spectrum sensing. In the proposed CioT, the frame is divided into sensing slot and transmission slot, and each cluster can perform either cooperative spectrum sensing or energy harvesting within sensing slot. A joint optimization problem of time and node is presented to maximize the spectrum access probability of the CIoT. A joint optimization algorithm is proposed to obtain the solution to the optimization problem. Then a clustering algorithm is proposed to allocate nodes and head to each cluster. Sensing and harvesting handoff of each cluster is analyzed and the minimal number of working nodes in a cluster is achieved to continue spectrum sensing. The simulations show that there is an optimal set of sensing time and number of sensing clusters to maximize the spectrum access probability, and there are tradeoffs between spectrum sensing, spectrum access and energy harvesting.

Keywords

Cognitive Internet of Things Cluster Energy harvesting Spectrum access Joint optimization 

Notes

Acknowledgements

This paper is supported by the National Natural Science Foundations of China under Grants 61601221, 61671183 and 61771163, the Joint Foundation of the National Natural Science Foundations of China and the Civil Aviation of China under Grant U1833102, and the China Postdoctoral Science Foundations under Grants 2015M580425 and 2018T110496.

References

  1. 1.
    Mitola J (2001) Cognitive radio for flexible mobile multimedia communications. Mobile Networks and Applications 6(5):435–441zbMATHCrossRefGoogle Scholar
  2. 2.
    Ghasemi A, Sousa ES (2008) Spectrum sensing in cognitive radio networks: requirements, challenges and design trade-offs. IEEE Commun Mag 46(4):32–39CrossRefGoogle Scholar
  3. 3.
    Liu X, Jia M, Na Z, Lu W, Li F (2018) Multi-modal cooperative spectrum sensing based on Dempster-Shafer fusion in 5G-based cognitive radio. IEEE Access 6:199–208CrossRefGoogle Scholar
  4. 4.
    Shen J, Liu S, Wang Y (2009) Robust energy detection in cognitive radio. IET Commun 3(6):1016–1023CrossRefGoogle Scholar
  5. 5.
    Liu X, Min J, Tan X (2013) Threshold optimization of cooperative spectrum sensing in cognitive radio network. Radio Sci 48(1):23–32CrossRefGoogle Scholar
  6. 6.
    Liu X, Jia M, Gu X, Tan X (2013) Optimal periodic cooperative spectrum sensing based on weight fusion in cognitive radio networks. Sensors 13(4):5251–5272CrossRefGoogle Scholar
  7. 7.
    Duan DL, Yang LQ, Principe JC (2010) Cooperative diversity of spectrum sensing for cognitive radio systems. IEEE Trans Signal Process 58(6):3218–3227MathSciNetzbMATHCrossRefGoogle Scholar
  8. 8.
    Liu X, Tan X (2014) Optimization algorithm of periodical cooperative spectrum sensing in cognitive radio. Int J Commun Syst 27(5):705–720CrossRefGoogle Scholar
  9. 9.
    Hamza D, Aissa S, Aniba G (2014) Equal gain combining for cooperative spectrum sensing in cognitive radio networks. IEEE Trans Wirel Commun 13(8):4334–4345CrossRefGoogle Scholar
  10. 10.
    Xia J, Zhou F, Lai X, et al. (2018) Cache aided decode-and-forward relaying networks from the spatial view. Wirel Commun Mob Comput 2018(5963584):1–9CrossRefGoogle Scholar
  11. 11.
    Fan L, Zhao N, Lei X, Chen Q, Yang N, Karagiannidis GK (2019) Outage probability and optimal cache placement for multiple amplify-and-forward relay networks. IEEE Trans. Vehicular Technology In press: 1–6Google Scholar
  12. 12.
    Liu X, Jia M (2017) Joint optimal fair cooperative spectrum sensing and transmission in cognitive radio. Physical Communication 25:445–453CrossRefGoogle Scholar
  13. 13.
    Liao Y, Wang T, Song L, Lingyang ZH (2017) Listen-and-talk: Protocol design and analysis for full-duplex cognitive radio networks. IEEE Trans Veh Technol 66(1):656–667Google Scholar
  14. 14.
    Liu X, Jia M, Gu X, Kong F, Jing Q (2014) Optimal joint allocation of multislot spectrum sensing and transfer power in multichannel cognitive radio. Journal of Sensors 2014(494361): 1–9Google Scholar
  15. 15.
    Liang Y, Zeng Y, Peh ECY, Hoang AT (2008) Sensing-throughput tradeoff for cognitive radio networks. IEEE Trans Wireless Commun 7(4):1326–1337CrossRefGoogle Scholar
  16. 16.
    Fan RF, Jiang H (2010) Optimal multi-channel cooperative sensing in cognitive radio networks. IEEE Trans Wireless Commun 9(3):1128–1138CrossRefGoogle Scholar
  17. 17.
    Liu X, Bi G, Guan YL, Lu W, Yan J, Zhong W (2015) Joint optimisation algorithm of cooperative spectrum sensing with cooperative overhead and sub-band transmission power for wideband cognitive radio network. Transactions on Emerging Telecommunications Technologies 26(4):586–597CrossRefGoogle Scholar
  18. 18.
    Liu X (2015) A novel wireless power transfer-based weighed clustering cooperative spectrum sensing method for cognitive sensor networks. Sensors 15(11):27760–27782CrossRefGoogle Scholar
  19. 19.
    Condry MW, Nelson CB (2016) Using smart edge IoT devices for safer, rapid response with industry IoT control operations. Proc IEEE 104(5):938–946CrossRefGoogle Scholar
  20. 20.
    Khalfi B, Hamdaoui B, Guizani M (2017) Exploiting inherent sparsity for efficient IoT support in 5G challenges and potential solutions. IEEE Wirel Commun 24(5):68–73CrossRefGoogle Scholar
  21. 21.
    Liu X, Jia M, Zhang X, Lu W (2018) A novel multi-channel Internet of Things based on dynamic spectrum sharing in 5G communication. IEEE Internet Things J In press: 1–9.  https://doi.org/10.1109/JIOT.2018.2847731 CrossRefGoogle Scholar
  22. 22.
    Jia M, Yin Z, Guo Q, Liu G, Gu X Downlink design for spectrum efficient IoT network. IEEE Internet Things J In press: 1–8.  https://doi.org/10.1109/JIOT.2017.2734815 CrossRefGoogle Scholar
  23. 23.
    Jia M, Li D, Yin Z, Guo Q, Gu X (2018) High spectral efficiency secure communications with non-orthogonal physical and multiple access layers. IEEE Internet Things J In press:1-8.  https://doi.org/10.1109/JIOT.2018.2851069 CrossRefGoogle Scholar
  24. 24.
    Liu X, Zhang X (2018) Rate and energy efficiency improvements for 5G-based IoT with simultaneous transfer. IEEE Internet Things J In press:1–9.  https://doi.org/10.1109/JIOT.2018.2863267 CrossRefGoogle Scholar
  25. 25.
    Daniel P, Payam B, Rahim T (2017) Adaptive clustering for dynamic IoT data streams. IEEE Internet Things J 4(1):64–74Google Scholar
  26. 26.
    Liu X, Li F, Na Z (2017) Optimal resource allocation in simultaneous cooperative spectrum sensing and energy harvesting for multichannel cognitive radio. IEEE Access 5:3801– 3812CrossRefGoogle Scholar
  27. 27.
    Lee S, Zhang R, Huang K (2013) Opportunistic wireless energy harvesting in cognitive radio networks. IEEE Trans Wirel Commun 12(9):4788–4799CrossRefGoogle Scholar
  28. 28.
    Park S, Kim H, Hong D (2013) Cognitive radio networks with energy harvesting. IEEE Trans Wirel Commun 12(3):1386– 1397CrossRefGoogle Scholar
  29. 29.
    Shi F, Fan L, Liu X, Na Z, Liu Y (2018) Probabilistic caching placement in the presence of multiple eavesdroppers. Wirel Commun Mob Comput 2018(2104162):1–10CrossRefGoogle Scholar
  30. 30.
    Liu X, Chen K, Yan J, Na Z (2016) Optimal energy harvesting-based weighed cooperative spectrum sensing in cognitive radio network. Mobile Networks and Applications 21(6):908– 919CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Information and Communication EngineeringDalian University of TechnologyDalianChina
  2. 2.School of Electronics and Information EngineeringHarbin Institute of TechnologyHarbinChina
  3. 3.School of Information Science and TechnologyDalian Maritime UniversityDalianChina

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